Colistin Resistance in Acinetobacter baumannii MDR-ZJ06 Revealed by a Multiomics Approach

Acinetobacter baumannii has emerged as an important opportunistic pathogen due to its ability to acquire resistance to most currently available antibiotics. Colistin is often considered as the last line of therapy for infections caused by multidrug-resistant A. baumannii (MDRAB). However, colistin-resistant A. baumannii strain has recently been reported. To explore how multiple drug-resistant A. baumannii responded to colistin resistance, we compared the genomic, transcriptional and proteomic profile of A. baumannii MDR-ZJ06 to the induced colistin-resistant strain ZJ06-200P5-1. Genomic analysis showed that lpxC was inactivated by ISAba1 insertion, leading to LPS loss. Transcriptional analysis demonstrated that the colistin-resistant strain regulated its metabolism. Proteomic analysis suggested increased expression of the RND efflux pump system and down-regulation of FabZ and β-lactamase. These alterations were believed to be response to LPS loss. In summary, the lpxC mutation not only established colistin resistance but also altered global gene expression.


INTRODUCTION
Acinetobacter baumannii has emerged as an important opportunistic pathogen due to its ability to acquire resistance to most currently available antibiotics (Peleg et al., 2008;Howard et al., 2012;Antunes et al., 2014). Since current treatment options for multi-drug resistant (MDR) A. baumannii are extremely limited, colistin is often considered as the last line of the therapy for infections caused by MDR A. baumannii (Bae et al., 2016;Cheah et al., 2016b). However, colistin-resistant A. baumannii strain has recently been reported (Cai et al., 2012).
Colistin is a polycationic antimicrobial peptide that targets the polyanionic bacterial lipopolysaccharide (LPS) of Gram-negative bacteria. Two different colistin resistance mechanisms have previously been reported (Beceiro et al., 2014). The first mechanism inactivates the lipid A biosynthesis pathway, leading to the complete loss of surface LPS. Mutations in lpxC, lpxA, or lpxD are involved in the first mechanism. The pmrAB two-component system mediates the second resistance mechanism. Mutations in pmrA and pmrB induce the activity of pmrC, which adds phosphoethanolamine (PEtn) to the hepta-acylated form of lipid A (Beceiro et al., 2011). Further mutations in vacJ, pldA, ttg2C, pheS and a conserved hypothetical protein were reported to involve in reduced colistin susceptibility through novel resistance mechanisms (Thi Khanh Nhu et al., 2016). Four putative colistin resistant genes: A1S_1983, hepA, A1S_3026, and rsfS were also identified in our previous study (Mu et al., 2016).
The response to LPS alteration has been investigated via transcriptional analysis. In response to LPS alteration, A. baumannii alters the expression of critical transport and biosynthesis systems associated with modulating the composition and structure of the bacterial surface (lpxA; Henry et al., 2012) or alters the expression of genes associated with outer membrane structure and biogenesis (pmrB; Cheah et al., 2016a). Moreover, the response to colistin is highly similar to the transcriptional alteration observed in an LPSdeficient strain (Henry et al., 2015). Colistin resistance was also explored using proteomic methods. There were 35 differentially expressed proteins. Most differentially expressed proteins were down-regulated in the colistin resistant strain, including outer membrane proteins, chaperones, protein biosynthesis factors, and metabolic enzymes (Fernandez-Reyes et al., 2009). However, the combination of genomic, transcriptomic, and proteomic methods to examine the colistin resistance mechanism in A. baumannii has rarely been reported. Furthermore, the strain used in this study was an MDR strain, but not laboratory strains (ATCC 19606, ATCC 17978) that do not represent clonal lineages in a clinical environment. Here, we used genome, transcriptome, and proteome to elucidate the colistin resistance mechanism in MDR A. baumannii. There was an ISAba1 insertion in lpxC (ABZJ_03720) in ZJ06-200P5-1 compared with the genome sequence of MDR-ZJ06,  where lpxC encoded an UDP-3-O-acyl-N-acetylglucosamine deacetylase.

Generation of Colistin-Resistant Mutant
A colistin-resistant mutant was generated in A. baumannii MDR-ZJ06 by a previously described method (Li et al., 2006    the cells were centrifuged at 14,000 × g for 30 min at 4 • C. The protein concentration in the supernatant was determined by the BCA method. In brief, 300 µg protein was added to 200 µl UA buffer (8 M urea, 150 mM Tris-HCl pH 8.0) and ultrafiltered (Sartorius, 10 kD) with UA buffer. To block reduced cysteine residues, 100 µl iodoacetamide (IAA) buffer (50 mM IAA in UA buffer) was added, centrifuged at 600 rpm for 1 min, and incubated for 30 min in the dark. The filter was washed twice with 100 µl UA buffer and twice with 100 µl Dissolution buffer (50 mM triethylammonium bicarbonate, pH 8.5). Finally, the proteins were digested with 2 µg trypsin (Promega) in 40 µl Dissolution buffer at 37 • C for 16-18 h. The peptides were collected as a filtrate, and its content was estimated at OD 280 .
For iTRAQ labeling, the peptides were labeled with the 4-plex iTRAQ reagent following the manufacturer's instructions (AB SCIEX). The peptides from MDR-ZJ06 were labeled with 114 and 116 isobaric reagents, and the peptides from ZJ06-200P5-1 were labeled with 115 and 117 isobaric reagents.
RP-HPCL online-coupled to MS/MS (LC-MS/MS) analysis of the iTRAQ-labeled peptides was performed on an EASY-nLC nanoflow LC system (Thermo Fisher Scientific) connected to an Orbitrap Elite hybrid mass spectrometer (Thermo Fisher Scientific). After the samples were reconstituted and acidified with buffer A (0.1% (v/v) formic acid in water), a set-up involving a pre-column and analytical column was used. The pre-column was a 2 cm EASY-column (100, 5 µm C18; Thermo Fisher Scientific), while the analytical column was a 10 cm EASYcolumn (75, 3 µm, C18; Thermo Fisher Scientific). The 120 min linear gradient from 0 to 100% buffer B (0.1% (v/v) formic acid and 80% acetonitrile) at a constant flow rate of 250 nl/min was as follows: 0-100 min, 0-35% buffer B; 100-108 min, 35-100% buffer B; 108-120 min, 100% buffer B. MS data were acquired using a data-dependent top 10 method, dynamically choosing the most abundant precursor ions from the survey scan (300-180 m/z) for HCD fragmentation. The Dynamic exclusion was set to a repeat count of 1 with a 30 s duration. Survey scans were acquired at a resolution of 30,000 at m/z 200, and the resolution for HCD spectra was set to 15,000 at m/z 200. The normalized collision energy was 35 eV, and the underfill ratio was defined as 0.1%.
The MS/MS spectra were searched using the MASCOT engine (Matrix Science, London, UK; version 2.2) against the A. baumannii MDR-ZJ06 FASTA database. False discovery rates (FDR) were calculated via running all spectra against the FASTA database using the MASCOT software. The following options were used to identify proteins: peptide mass tolerance = 20 ppm, fragment mass tolerance = 0.1 Da, Enzyme = Trypsin, Max missed cleavages = 2, Fixed modification: Carbamidomethyl (C), iTRAQ 4plex (N-term), iTRAQ 4plex (K), Variable modification: Oxidation (M). Quantification was performed based on the peak intensities of the reporter ions in the MS/MS spectra. The proteins were considered overexpressed when the iTRAQ ratio was above 1.5 and underexpressed when the iTRAQ ratio was lower than 0.67 . Functional classification of differentially expression genes were annotated using the KEGG databases. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (Vizcaino et al., 2016) partner repository with the dataset identifier PXD005265 and 10.6019/PXD005265. Reviewer account details: Username: reviewer54242@ebi.ac.uk; Password: zR8mE9wu.

Growth Rate Determination
Four independent cultures per strain were grown overnight, diluted to 1:1000 in MH and aliquots placed into a flat-bottom 100-well plate in four replicates. The plate was incubated at 37 • C with agitation. The OD 600 of each culture was determined every 5 min for 16 h using a Bioscreen C MBR machine (Oy Growth Curves Ab Ltd., Finland). The growth rate was estimated based on OD 600 curves using an R script (Fang et al., 2016).

Transcriptome Analysis
The transcriptome analysis of ZJ06-200P5-1 and MDR-ZJ06 was performed by Illumina RNA deep sequencing technology. Cells of the two strains were collected in the early exponential phase. A total of 137 genes showed significant differential expression [log2(FoldChange) > 1 or log2(FoldChange) < −1], among which 48 genes were upregulated and 89 were downregulated ( Table 2). Sixteen selected genes, three upregulated and thirteen down-regulated genes, were well-validated by RT-qPCR (Figure 2). After mapping the differentially expressed genes into the KEGG pathway, we observed that genes involved in Energy metabolism and Amino acid metabolism were down-regulated, while Carbohydrate metabolism was up-regulated. iTRAQ A total of 1582 proteins were identified in the iTRAQ experiment. A protein ratio >1.5 or <0.67 (p < 0.05) was considered to be differentially expressed. After filtration, 82 differentially expressed proteins were identified between ZJ06-200P5-1 and MDR-ZJ06. The detailed information is shown in Table 3.
The fatty acid biosynthesis pathway was down-regulated in the ZJ06-200P5-1 strain ( Figure 3B)

Common Genes Altered Expression in Both Transcriptome and Proteome
A total of 15 differentially expressed genes (or proteins) were identified in both transcriptome and proteome ( Table 4). Among them, three genes were both up-regulated, and nine genes were both down-regulated. Although there was correlation between transcriptome and proteome data, the absolute expression difference values in transcriptome data was higher than those in proteome data. In addition, the result of three gene/proteins were contradictory (highlighted in red letters in Table 4). The contradictory result might be caused by post-transcriptional regulation.

DISCUSSION
Due to the limitation of antimicrobial agents in clinical use, it is urgent to extend our understanding of the emergence of colistin resistance in A. baumannii. A. baumannii MDR-ZJ06, a multidrug-resistant clinical strain isolated from bloodstream, has been sequenced and was considered an ideal strain for examining the colistin-resistant mechanism in A. baumannii (Zhou et al., 2011). In this study, colistin-resistant strain was rapidly obtained, and its resistance mechanism was LPS loss caused by ISAba1 insertion in lpxC. This result confirmed a previous finding (Moffatt et al., 2010). The rapid isolation of colistin-resistant mutant from multiple drug-resistant A. baumannii indicated a high risk of A. baumannii evolving resistance to colistin in clinical use.
We successfully detected the whole transcriptional profile of A. baumannii strain MDR-ZJ06 and its colistinresistant mutant ZJ06-200P5-1 via Illumina RNA-sequencing. In another transcriptome study (Henry et al., 2012), A. baumannii ATCC 19606 and its lpxA mutant were used. Although both the lpxC and lpxA mutation lead to LPS loss, the different transcriptional response may be due to differences in the strain genetic background and the resistant mutation. In transcriptional analysis, we observed that genes involved in Energy metabolism and Amino acid metabolism were down-regulated, while Carbohydrate metabolism was up-regulated.
The expression of AdeABC was up-regulated in the LPS-loss ZJ06-200P5-1 strain. Similar results were also observed in all polymyxin-treated samples (Cheah et al., 2016a). In addition, the expression levels of adeIJK and macAB-tolC were up-regulated in the LPS loss mutant (Henry et al., 2012). Increased expression of the RND efflux pump system (AdeABC) was a common finding across all experiments in colistin exposure. The up-regulation of AdeABC indicated the diminished integrity and barrier function of the outer membrane in colistin-resistant A. baumannii (Henry et al., 2015;Cheah et al., 2016a). However, ZJ06-200P5-1 showed higher susceptibility to multiple antibiotics than MDR-ZJ06. The higher susceptibility might result from the higher outer membrane permeability of ZJ06-200P5-1 due  to LPS-loss. The increased expression of the efflux pump was thought to be a response to toxic substances that accumulated in the cells due to the increased membrane permeability (Henry et al., 2012). The fatty acid biosynthesis pathway was down-regulated in the ZJ06-200P5-1 strain. In E. coli, it is important to balance LPS and fatty acid biosynthesis to maintain cell integrity. FabZ, which dehydrates R-3-hydroxymyristoyl-acyl carrier protein in fatty acid biosynthesis, plays an important role in rebalancing lipid A and fatty acid homeostasis (Bojkovic et al., 2016). The decrease in FabZ was considered to be a response to LPS-loss in ZJ06-200P5-1. The β-lactamases bla OXA−23 and bla ADC−25 were down-regulated in the ZJ06-200P5-1 strain. Decreased expression levels of bla OXA−23 and bla ADC−25 were also observed in A. baumannii MDR-ZJ06 under a subinhibitory concentration of tigecycline (Hua et al., 2014). Meanwhile, the strain under tigecycline stress showed a lower MIC of ceftazidime (Hua et al., 2014). The decrease in bla OXA−23 and bla ADC−25 might contribute to the increased sensitivity to β-lactam antimicrobial agents.
A multi-omics approach was adopted to obtain a more global view of colistin-resistant A. baumannii. Genomic analysis showed that lpxC was inactivated by ISAba1 insertion, leading to LPS loss. Transcriptional analysis demonstrated that the colistinresistant strain regulated its metabolism. Metabolic change and LPS loss were concomitant. Proteomic analysis suggested increased expression of the RND efflux pump system and the down-regulation of FabZ and β-lactamase. These alterations are believed to be responses to LPS loss. Together, the lpxC mutation not only confirmed colistin resistance but also altered global gene expression.

Nucleotide Sequence Accession Numbers
The whole-genome shotgun sequencing results for A. baumannii ZJ06-200P5-1 have been deposited at DDBJ/EMBL/GenBank under the accession number MIFW00000000.

AUTHOR CONTRIBUTIONS
XH and YY conceived and designed the study. XH, LL, YF, QS, XL, QC, KS, YJ, and HZ performed the experiments. XH and YY performed data analysis and drafted the manuscript. All authors reviewed and approved the final manuscript.